基于机器学习的内孤立波遥感探测研究综述

A Review on Remote Sensing of Internal Solitary Waves Based on Machine Learning

摘要:

海洋内孤立波是一种在稳定层化海水内部广泛分布的波动，对物质能量传输和海洋环流具有重要作用，也对海洋工程建设和舰船航行安全产生了重要影响。机器学习技术利用数据训练模型，使计算机具备学习和改进性能的能力，在图像检测、分割和预测等领域得到广泛应用。探讨了机器学习在内孤立波检测识别、参数反演和传播预测方面的应用，并指出当前研究中存在的问题，如内孤立波数据集和专门算法研究不足等。最后，分析了机器学习在内孤立波研究中的未来发展趋势。

Abstract:

Oceanic internal solitary waves are widely distributed within the stratified layers of seawater, playing a crucial role in the transfer of material energy and oceanic circulation. They also have an important impact on ocean engineering construction and ship navigation safety. Machine learning technology utilizes data to train models, enabling computers to possess the capability of learning and improving performance, and is widely used in areas such as image detection, segmentation and prediction. This paper discusses the application of machine learning in internal solitary detection and recognition, parameter inversion and propagation prediction, and points out current research issues, such as insufficient research on internal solitary wave datasets and specialized algorithm. Finally, the future development trend of machine learning in internal solitary waves is analyzed.